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ZHOU Rui, ZOU Minghao, ZHOU Wenxuan, LIU Fuchen, ZHANG Kaiting, WU Xiaoqin, ZHAO Man, QIAN Jin, JIA Ningyang, LIU Hui. Morphological characteristics of hepatocellular carcinoma tumor margin: a crucial factor in clinical treatment decision-making and prognostic assessment[J]. Journal of Clinical Medicine in Practice, 2025, 29(7): 127-130, 137. DOI: 10.7619/jcmp.20245496
Citation: ZHOU Rui, ZOU Minghao, ZHOU Wenxuan, LIU Fuchen, ZHANG Kaiting, WU Xiaoqin, ZHAO Man, QIAN Jin, JIA Ningyang, LIU Hui. Morphological characteristics of hepatocellular carcinoma tumor margin: a crucial factor in clinical treatment decision-making and prognostic assessment[J]. Journal of Clinical Medicine in Practice, 2025, 29(7): 127-130, 137. DOI: 10.7619/jcmp.20245496
shu

Morphological characteristics of hepatocellular carcinoma tumor margin: a crucial factor in clinical treatment decision-making and prognostic assessment

  • 1.

    School of Health Sciences and Engineering of University of Shanghai for Science and Technology, Shanghai, 200093

  • 2.

    the Third Department of Hepatic Surgery, the Third Affiliated Hospital of Naval Medical University, Shanghai, 200438

  • 3.

    Department of Radiology, the Third Affiliated Hospital of Naval Medical University, Shanghai, 200438

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  • Received Date: November 11, 2024
  • Revised Date: December 25, 2024
    Graphical Abstract
    • Abstract

  • The morphological characteristics of hepatocellular carcinoma (HCC) tumor margins are pivotal in influencing patient's prognosis and the selection of therapeutic strategies. This paper reviewed the classification methods of HCC tumor margins, ranging from traditional macroscopic classifications to refined classification systems based on multi-omics analysis, and analyzed the role of these classification methods in guiding the formulation of personalized treatment plans. Additionally, this paper emphasized the crucial role of three-dimensional imaging techniques in assessing tumor margin morphology and outlined future research directions, including validating the effectiveness of multi-omics classification systems and developing new imaging and molecular biomarkers to achieve more precise treatment plans and prolong patient survival.

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    • References (43)
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